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The high cost and competitive nature of automotive product development necessitates the search for less expensive and faster methods of predicting vehicle performance. Continual improvements in High Performance Computing (HPC) and new computational schemes allow for the digital evaluation of vehicle comfort parameters including wind noise. Recently, the commercially available Computational Fluid Dynamics (CFD) code PowerFlow, was evaluated for its accuracy in predicting wind noise generated by an external automotive tow mirror. This was accomplished by running simulations of several mirror configurations, choosing the quietest mirror based on the predicted performance, prototyping it, and finally, confirming the prediction with noise measurements taken in an aeroacoustic wind tunnel. Two testing methods, beam-forming and direct noise measurements, were employed to correlate the physical data with itself before correlating with simulation.

This paper presents a simulation of the cooling airflow and surface temperatures of a midsize truck. The simulation uses full detailed geometry of the truck. Performance of the under-hood cooling airflow is analyzed and potential design changes leading to better cooling airflow are highlighted. Surface temperature over certain under-hood part is studied. Possible optimizations using various material and configurations are proposed. It is shown that the presented simulation approach provides valuable information to evaluate cooling system and thermal protection performance. Fast design iterations can be achieved using this approach.

One of the remaining challenges in the simulation of the aerodynamics of ground vehicles is the modeling of the airflows around the spinning tires and wheels of the vehicle. As in most advances in the development of simulation capabilities, it is the lack of appropriately detailed and accurate experimental data with which to correlate that holds back the advance of the technology. The flow around the wheels and tires and their interfaces with the vehicle body and the ground is a critical area for the development of automobiles and trucks, not just for aerodynamic forces and moments, and their result on fuel economy and vehicle handling and performance, but also for the airflows and pressures that affect brake cooling, engine cooling airflows, water spray management etc.

As vacuum suction cups are widely used in stamping plants, it becomes urgent and important to understand their performance and failure mode. Vacuum suction cups are employed to lift, move, and place sheet metal instead of human hands. Occasionally the vacuum cups would fail and drop parts, even it would cause expensive delays in the production line. In this research, several types of vacuum cups have been studies and compared experimentally. A new tensile device and test method was developed to measure the pulling force and deformation of vacuum cups. The digital image correlation technique has been adopted to capture and analyze the contour, deformation and strain of the cups under different working conditions. The experimental results revealed that the relevant influential parameters include cup type, pulling force angles, vacuum levels, sheet metal curvatures, etc.

Self-piercing riveting (SPR) has been used in production to join sheet materials since the early 1990s. A large amount of experimental trial work was required in order to determine an appropriate combination of rivet and anvil design to fulfill the required joint parameters. The presented study is describing the methodology of SPR joint design based on numerical simulation and experimental methods of defining required simulation input parameters. The required inputs are the stress-strain curves of sheet materials and rivets for the range of strains taking place in the SPR joining process, parameters required for a fracture model for all involved materials, and friction parameters for all interfaces of SPR process. In the current study, the normalized Cockroft-Latham fracture criterion was used for predicting fracture. Custom hole and tube expansion tests were used for predicting fracture of the riveted materials and the rivet, respectively.

The engineering process in the development of commercial vehicles is facing more and more stringent emission regulations while at the same time the market demands for better performance but with lower fuel consumption. The optimization of aerodynamic performance for reduced drag is a key element for achieving related performance targets. Closely related to aerodynamics are wind noise and cabin soiling and both of them are becoming more and more important as a quality criterion in many markets. This paper describes the aerodynamic and aero-acoustic performance evaluation of a Dongfeng heavy truck using digital simulation based on a LBM approach. It includes a study for improving drag within the design of a facelift of the truck. A soiling analysis is performed for each aerodynamic result by calculating the accumulation of particles emitted form the wheels on the cabin. One of the challenges in the development process of trucks is that different cabin types have to be designed.

Long haul tractor design in the future will be challenged by freight efficiency standards and emission legislations. Along with any improvements in aerodynamics, this will also require additional cooling capacity to handle the increased heat rejection from next generation engines, waste heat recovery and exhaust gas recirculation systems. Fan engagement will also have to be minimized under highway conditions to maximize fuel economy. These seemingly contradictory requirements will require design optimization via analysis techniques capable of predicting both the aerodynamic drag and engine cooling airflow accurately. This study builds on previous work [1] using a Lattice Boltzmann based computational method on a Volvo VNL tractor trailer combination. Simulation results are compared to tests conducted at National Research Council (NRC) Canada's wind tunnel.

Water accumulating on a vehicle's wind screen, driven over the A-pillar by a combination of aerodynamic forces and the action of the windscreen wipers, can be a significant impediment to driver vision. Surface water film, or streams, persisting in key vision areas of the side glass can impair the drivers' ability to see clearly through to the door mirror, and laterally onto junctions. Common countermeasures include: water management channels and hydrophobic glass coatings. Water management channels have both design and wind noise implications. Hydrophobic coatings entail significant cost. In order to manage this design optimisation issue a water film and wiper effect model has been developed in collaboration with Jaguar Land Rover, extending the capabilities of the PowerFLOW CFD software. This is complimented by a wind-tunnel based test method for development and validation. The paper presents the progress made to date.

In this paper, the development of random vibration testing schedules for durability design verification of engine mounted products is presented, based on the equivalent fatigue damage concept and the 95th-percentile customer engine usage data for 150,000 miles. Development of the 95th-percentile customer usage profile is first discussed. Following that, the field engine excitation and engine duty cycle definition is introduced. By using a simplified transfer function of a single degree-of-freedom (SDOF) system subjected to a base excitation, the response acceleration and stress PSDs are related to the input excitation in PSD, which is the equivalent fatigue damage concept. Also, the narrow-band fatigue damage spectrum (FDS) is calculated in terms of the input excitation PSD based on the Miner linear damage rule, the Rayleigh statistical distribution for stress amplitude, a material's S-N curve, and the Miles approximate solution.

A validation study was performed comparing the simulation results of the Lattice-Boltzmann Equation (LBE) based flow solver, PowerFLOW®, to cooling cell measurements conducted at Volvo Trucks North America (VTNA). The experimental conditions were reproduced in the simulations including dynamometer cell geometry, fully detailed under-hood, and external tractor geometry. Interactions between the air flow and heat exchangers were modeled through a coupled simulation with the 1D-tool, PowerCOOL™, to solve for engine coolant and charge air temperatures. Predicted temperatures at the entry and exit plane of the radiator and charge-air-cooler were compared to thermocouple measurements. In addition, a detailed flow analysis was performed to highlight regions of fan shroud loss and cooling airflow recirculation. This information was then used to improve cooling performance in a knowledge-based incremental design process.

The accuracy of the Lattice-Boltzmann based simulation method for prediction of aerodynamic drag on a heavy truck was evaluated by comparing results to twenty percent scale model wind tunnel measurements from the University of Washington Aeronautical Laboratory (UWAL). A detailed preproduction Kenworth T2000 tractor trailer was used as the scale model. The results include a comparison of normalized drag between simulation and wind tunnel as well as percentage drag change with the addition of a radius to the rear edge of the trailer. Significant effort was involved to model all of the wind tunnel details affecting the tractor-trailer drag. These are discussed along with the results of additional simulations which were performed to study the impact of the UWAL tunnel geometry relative to a tunnel with the same blockage and constant cross-sectional area, and a case with negligible blockage.

During the design process for a vehicle, the CAD surface geometry becomes available at an early stage so that numerical assessment of aerodynamic performance may accompany the design of the vehicle's shape. Accurate prediction requires open grille models with detailed underhood and underbody geometry with a high level of detail on the upper body surface, such as moldings, trim and parting lines. These details are also needed for aeroacoustics simulations to compute wall-pressure fluctuations, and for thermal management simulations to compute underhood cooling, surface temperatures and heat exchanger effectiveness. This paper presents the results of a significant effort to capitalize on the investment required to build a detailed virtual model of a pickup truck in order to simultaneously assess performance factors for aerodynamics, aeroacoustics and thermal management.

The engineering process in the development of commercial vehicles is facing more and more stringent emission regulations while at the same time the market demands for better performance but with lower fuel consumption and higher reliability. Respective targets require better utilization of existing or even higher engine cooling capacity and optimization of aerodynamic performance for reduced drag. In order to aid on achieving both goals, special attention should be paid on understanding both external and under hood flow structures. This paper describes an optimization study for reducing aerodynamic drag and increasing engine cooling performance conducted on a Light Truck at Jiangling Motors Corporation (JMC). The approach is using simulation based on a LBM solver coupled with a heat exchanger model. Such methodology was used to predict both aerodynamic and cooling characteristics and help highlighting potential areas for improvement.

The importance of fuel economy and emission standards has increased rapidly with high fuel costs and new environmental regulations. This requires analysis techniques capable of designing the next generation long-haul truck to improve both fuel efficiency and cooling. In particular, it is important to have a predictive design tool to assess how exterior design changes impact aerodynamic performance. This study evaluates the use of a Lattice Boltzmann based numerical simulation and the National Research Council (NRC) Canada's wind tunnel to assess aerodynamic drag on a production Volvo VNL tractor-trailer combination. Comparisons are made between the wind tunnel and simulation to understand the influence of wind tunnel conditions on truck aerodynamic performance. The production VNL testing includes a full range of yaw angles to demonstrate the influence of cross wind on aerodynamic drag.

Side window clarity and its effect on side mirror visibility plays a major role in driver comfort. Driving in inclement weather conditions such as rain can be stressful, and having optimal visibility under these conditions is ideal. However, extreme conditions can overwhelm exterior water management devices, resulting in rivulets of water flowing over the a-pillar and onto the vehicle’s side glass. Once on the side glass, these rivulets and the pooling of water they feed, can significantly impair the driver’s ability to see the side mirror and to see outwardly when in situations such as changing lanes. Designing exterior water management features of a vehicle is a challenging exercise, as traditionally, physical testing methods first require a full-scale vehicle for evaluations to be possible. Additionally, common water management devices such as grooves and channels often have undesirable aesthetic, drag, and wind noise implications.

The aerodynamics of a rotating tire can contribute up to a third of the overall aerodynamic force on the vehicle. The flow around a rotating tire is very complex and is often affected by smallest tire features. Accurate prediction of vehicle aerodynamics therefore requires modeling of tire rotation including all geometry details. Increased simulation accuracy is motivated by the needs emanating from stricter new regulations. For example, the upcoming Worldwide harmonized Light vehicles Test Procedures (WLTP) will place more emphasis on vehicle performance at higher speeds. The reason for this is to bring the certified vehicle characteristics closer to the real-world performance. In addition, WLTP will require reporting of CO2 emissions for all vehicle derivatives, including all possible wheel and tire variants. Since the number of possible derivatives can run into the hundreds for most models, their evaluation in wind tunnels might not be practically possible.

Existing methods for design optimization under uncertainty assume that a high level of information is available, typically in the form of data. In reality, however, insufficient data prevents correct inference of probability distributions, membership functions, or interval ranges. In this article we use an engine design example to show that optimal design decisions and reliability estimations depend strongly on uncertainty characterization. We contrast the reliability-based optimal designs to the ones obtained using worst-case optimization, and ask the question of how to obtain non-conservative designs with incomplete uncertainty information. We propose an answer to this question through the use of Bayesian statistics. We estimate the truck's engine reliability based only on available samples, and demonstrate that the accuracy of our estimates increases as more samples become available.

Light-weighting vehicles cause an increase in Aluminum Alloy stamping processes in the Automotive Industry. Surface finish and lubricants of aluminum alloy (AA) sheet play an important role in the deep drawing processes as they can affect the friction condition between the die and the sheet. This paper aims to develop a reliable and practical laboratory test method to experimentally investigate the influence of surface finish, lubricant conditions, draw-bead clearances and pulling speed on the frictional sliding behavior of AA 6XXX sheet metal. A new double-beads draw-bead-simulator (DBS) system was used to conduct the simulated test to determine the frictional behavior of an aluminium alloy with three surface lubricant conditions: mill finish (MF) with oil lube, electric discharge texture (EDT) finish with oil lube and mill finish (MF) with dry lube (DL).

Fatigue strength mean and standard deviation may be estimated by the Probit and 2-Point test methods. In this paper, methodologies for conducting the tests are developed and results from Monte Carlo simulation are presented. The results are compared with those from concurrent testing with the staircase method. While the Probit and 2-Point methods are intuitively attractive, their results are significantly different from those from the staircase method. The latter remains the best of the three.

Mobility in the automotive and transportation sectors has been experiencing a period of unprecedented evolution. A growing need for efficient, clean and safe mobility has increased momentum toward sustainable technologies in these sectors. Toward this end, battery electric vehicles have drawn keen interest and their market share is expected to grow significantly in the coming years, especially in light-duty applications such as passenger cars. Although the battery electric vehicles feature high performance and zero tailpipe emission characteristics, economic and technical issues such as battery cost, driving range, recharging time and infrastructure remain main hurdles that need to be fully addressed. In particular, the low power density of the battery limits its broad adoption in heavy-duty applications such as class 8 semi-trailer trucks due to the required size and weight of the battery and electric motor.